Super easy Python stock price forecasting(using Support vector machine) Machine learning

1. tool installation

$ pip install scikit-learn pandas_datareader

2. file creation

3. execution

$ python pred.py

That’s super easy!

4. result

As a result of calculation with the same data and features, MLP are the best among XGBoost, DNN, LSTM, GRU, RNN, LogisticRegression, k-nearest neighbor, RandomForest, BernoulliNB, SVM, RGF, MLP, Bagging, Voting, Stacking.

XGBoost            0.5119047619047619
DNN 0.5496031746031746
LSTM 0.5178571428571429
GRU 0.5138888888888888
RNN 0.5376984126984127
LogisticRegression 0.5496031746031746
k-nearest neighbor 0.5198412698412699
RandomForest 0.49603174603174605
BernoulliNB 0.5496031746031746
SVM 0.5396825396825397
RGF 0.5158730158730159
MLP 0.5694444444444444
Bagging 0.5297619047619048
Voting 0.5416666666666666
Stacking 0.5218253968253969

5. reference

--

--

--

https://github.com/10mohi6

Love podcasts or audiobooks? Learn on the go with our new app.

Recommended from Medium

Laravel Throttles logins

10 Tips for Using Couplings in your Application

Running Obyte wallet on headless RaspberryPi 3+

Gem from Gematria Galaxy

TechTalk: Type Checking in Python

Basics of Selenium…

Authentication vs Authorization

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
10mohi6

10mohi6

https://github.com/10mohi6

More from Medium

A beginners guide to clustering using Python (Part-1)

Data Science for Industry: Hydropower Condition Monitoring and Predictive Maintenance

Python: Why axis = 0 leads to column wise Mean/Sum, but row wise drop/deletion?

Predicting State of Health and Lifecycle of Li-ion Batteries (pt.2)